Update app.py

app.py

@@ -15,20 +15,16 @@ def analyze_video(video_path, max_speakers, progress=gr.Progress()):
     if not video_path:
         return [gr.Markdown("Please upload a video file.")] + [gr.update(visible=False)] * 48 + ["Analysis not started.", ""]
 
-    # Start the progress bar
     progress(0, desc="Starting analysis...")
 
-    # Progress for transcription and diarization
     progress(0.2, desc="Starting transcription and diarization")
     transcription = diarize_audio(video_path, max_speakers)
     progress(0.6, desc="Transcription and diarization complete.")
 
-    # Progress for processing the transcription
     progress(0.7, desc="Processing transcription")
     results = process_input(transcription, llm)
     progress(0.8, desc="Transcription processing complete.")
 
-    # Progress for creating charts
     progress(0.9, desc="Generating charts")
     charts, explanations = create_charts(results)
     progress(1.0, desc="Charts generation complete.")
@@ -36,13 +32,9 @@ def analyze_video(video_path, max_speakers, progress=gr.Progress()):
     end_time = time.time()
     execution_time = end_time - start_time
 
-    # Prepare outputs for each speaker
     output_components = []
-    speaker_count = len(charts)
-
     for speaker_id, speaker_charts in charts.items():
         speaker_explanations = explanations[speaker_id]
-    
         speaker_section = [
             gr.Markdown(f"### {speaker_id}", visible=True),
             gr.Plot(value=speaker_charts.get("attachment", None), visible=True),
@@ -53,30 +45,16 @@ def analyze_video(video_path, max_speakers, progress=gr.Progress()):
             gr.Plot(value=speaker_charts.get("personality", None), visible=True),
             gr.Textbox(value=speaker_explanations.get("personality", ""), label="Personality Disorders Explanation", visible=True),
         ]
-    
         output_components.extend(speaker_section)
 
-    # Add empty placeholders for remaining outputs if fewer speakers than expected
     while len(output_components) < 48:
-        output_components.extend([
-            gr.Markdown(visible=False),
-            gr.Plot(visible=False),
-            gr.Textbox(visible=False),
-            gr.Plot(visible=False),
-            gr.Plot(visible=False),
-            gr.Textbox(visible=False),
-            gr.Plot(visible=False),
-            gr.Textbox(visible=False),
-        ])
+        output_components.extend([gr.update(visible=False)] * 8)
 
-    # Add the execution time
     output_components.append(gr.Textbox(value=f"Completed in {int(execution_time)} seconds.", label="Execution Information", visible=True))
+    output_components.append(gr.Textbox(value=transcription, label="Transcript", lines=10, visible=True))
 
-    # Return output_components and transcription separately
-    return output_components + [transcription]
+    return output_components
 
-# Define the Gradio interface
-# Define the Gradio interface
 with gr.Blocks() as iface:
     gr.Markdown("# AI Personality Detection")
     gr.Markdown("Upload a video")
@@ -86,9 +64,8 @@ with gr.Blocks() as iface:
 
     analyze_button = gr.Button("Analyze")
 
-    # Create placeholders for output components
     output_components = []
-    for _ in range(3):  # Assuming maximum of 3 speakers
+    for _ in range(3):
         output_components.extend([
             gr.Markdown(visible=False),
             gr.Plot(visible=False),
@@ -100,13 +77,9 @@ with gr.Blocks() as iface:
             gr.Textbox(label="Personality Disorders Explanation", visible=False),
         ])
 
-    # Add execution info box
     execution_info_box = gr.Textbox(label="Execution Information", value="Waiting for analysis...", lines=2)
-    output_components.append(execution_info_box)
-
-    # Add transcript output
     transcript_output = gr.Textbox(label="Transcript", lines=10, visible=True)
-    output_components.append(transcript_output)
+    output_components.extend([execution_info_box, transcript_output])
 
     analyze_button.click(
         fn=analyze_video,
@@ -115,6 +88,5 @@ with gr.Blocks() as iface:
         show_progress=True
     )
 
-# Launch the app
 if __name__ == "__main__":
     iface.launch()